Journal: NeuroImage

Article Title: Neuroanatomical morphometric characterization of sex differences in youth using statistical learning

doi: 10.1016/j.neuroimage.2018.01.065

Figure Lengend Snippet: Evaluation of the SVM model of neuroanatomical sex differences on an independent dataset (PING). (a) Receiver operating characteristic (ROC) curves from cross-validation accuracy test of the model building stage on the PNC dataset. Blue line is the ROC curve of the model of neuroanatomical sex differences and red line presents chance. (b) Confusion matrix based on the performance of the model in predicting the sex of subjects of the PING dataset. TP: true positive, FP: false positive, FN: false negative, TN: true negative. (c) prediction accuracies (y-axis) of the following (x-axis): the model of sex differences (blue bar), the gold standard and the baseline models (gray bars). For all 3 bars, the mean and standard deviation of 100 repetitions are plotted.

Article Snippet: Calculations involving the SVM model and the assessment of its performance were performed using MATLAB (Release, 2016a; The MathWorks, Inc.,) statistics and machine learning toolbox.

Techniques: Biomarker Discovery, Standard Deviation

Journal: NeuroImage

Article Title: Neuroanatomical morphometric characterization of sex differences in youth using statistical learning

doi: 10.1016/j.neuroimage.2018.01.065

Figure Lengend Snippet: Statistical inferences as derived from the generalized linear model (GLM) and support vector machine (SVM) model. T-statistics of GLM (top row) and beta coefficients of SVM (bottom row) are derived from the cortical surface area, mean curvature, cortical thickness and cortical volume using the Destrieux atlas. Supplementary Files 2 and 3 contain full lists of the GLM and the SVM statistics, respectively.

Article Snippet: Calculations involving the SVM model and the assessment of its performance were performed using MATLAB (Release, 2016a; The MathWorks, Inc.,) statistics and machine learning toolbox.

Techniques: Derivative Assay, Plasmid Preparation

Journal: NeuroImage

Article Title: Neuroanatomical morphometric characterization of sex differences in youth using statistical learning

doi: 10.1016/j.neuroimage.2018.01.065

Figure Lengend Snippet: Visualization of neuroanatomical differences of sex by combining the following three statistical values: Correlation of the neuroanatomical features with brain size as assessed by estimating Spearman's correlation with estimated total intracranial volume (x-axis), sex-related discriminatory indices derived from the SVM model (y-axis), and the univariate sex-related differences obtained from the GLM analysis (radius of spheres = negative log of the p-value). Pls: Paracentral lobule and sulcus, aMCC: Middle-anterior part of the cingulate cortex, mOG: Medial occipital gyrus, AG: angular gyrus, PP: Planum polare of the superior temporal gyrus, sPL: Superior parietal lobe, WM: white matter hemisphere. Superscripts refers to left (L), right (R) hemispheres. Interactive version of the plot is presented online on the Plotly website (https://plot.ly/~sepehrband/50/neuroanatomy-of-sex-difference/).

Article Snippet: Calculations involving the SVM model and the assessment of its performance were performed using MATLAB (Release, 2016a; The MathWorks, Inc.,) statistics and machine learning toolbox.

Techniques: Derivative Assay